Recent advances in 3 G/4 G wireless networks have significantly improved the bandwidth of wireless networks. It is envisioned that the IMT-advanced (the official name of 4 G by ITU-R) will support peak data rates of 100 Mbps for high mobility services and 1 Gbps for low mobility services. As a result, streaming of multimedia content such as video and audio over the Internet with a 4 G wireless last hop becomes a reality. However, high channel error rate and variable channel bandwidth are fundamental characteristics of wireless networks. Even the latest wireless networking standards do not provide sufficient support for QoS sensitive multimedia applications. Moreover, multimedia content and data packets often have different QoS requirements. Multimedia packets are generally error tolerant but delay sensitive while data packets are often error intolerant but delay insensitive. Therefore, they need to be treated differently over the Internet and especially over the wireless hop.
An important problem in streaming media is how to adapt the transmission rate to variable network conditions. One approach is to adapt the source rate to match the channel rate. In theory, this is the optimal way to adapt to channel condition if the channel rate is known precisely ahead of time. In practice, this approach incurs a large delay on the adaptation as the channel state information needs to be sent to the multimedia server and multimedia server has to wait for the next clear point (e.g., I-frame) in order to switch to a different rate. In addition, there is often only a limited number of source rates available at the video server, which cannot match exactly the channel bandwidth. As the channel conditions keep on changing, this may keep the video server oscillating between different coding rates.
In the past few years, work has been done on the rate-adaption of video streaming. For example, one approach optimizes the Lagrangian function of rate and distortion and provides an iterative procedure to find a sub-optimal solution of the problem. The Lagrangian function represents a trade-off between the rate and distortion for video transmission. In another solution, network congestion measured by the delay is used to replace the rate in the Lagrangian function to optimize the tradeoff between network congestion and the distortion. In yet another approach, each packet is assigned a re-transmission deadline and the packet is re-transmitted until its deadline has passed.